Uncertainty- and hardness-weighted loss functions for medical image segmentation. [PDF]
Zheng Y +7 more
europepmc +1 more source
A novel rumor detection with multi-objective loss functions in online social networks. [PDF]
Wan P, Wang X, Pang G, Wang L, Min G.
europepmc +1 more source
Loss functions for spatial wildfire applications
Spatial predictions of wildfire spread are used operationally and in risk estimation. It is important that their outputs are validated to quantify predictive performance and uncertainty.
Parkins, K +6 more
core +1 more source
Loss of proton‐sensing TDAG8 increases tumor progression in mouse models of colon cancer
Loss of the pH‐sensing receptor TDAG8 accelerates colorectal cancer progression in mice. Animals lacking TDAG8 expression had increased tumor growth, DNA damage, and recruitment of tumor‐associated immune cells, including macrophages, neutrophils, and monocytes.
Ermanno Malagola +11 more
wiley +1 more source
Deep learning-based dose prediction in proton beam therapy for hepatocellular carcinoma: comparison of network architectures and loss functions. [PDF]
Ogawa S +8 more
europepmc +1 more source
Novel loss functions for ensemble-based medical image classification. [PDF]
Rajaraman S, Zamzmi G, Antani SK.
europepmc +1 more source
Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller +10 more
wiley +1 more source
Low-Light Image Enhancement Using Hybrid Deep-Learning and Mixed-Norm Loss Functions. [PDF]
Oh J, Hong MC.
europepmc +1 more source
Transformation kernel density estimation of actuarial loss functions
A transformation kernel density estimator that is suitable for heavy-tailed distributions is discussed. Using a truncated Beta transformation, the choice of the bandwidth parameter becomes straightforward.
Montserrat Guillen (Universitat de Barcelona) +2 more
core
Comparison of our proposed loss with other common loss functions.
Comparison of our proposed loss with other common loss functions.
Yingjie Zhu (240610) +1 more
core +1 more source

